Nursing is the field in medicine that focuses on the care of individuals, families, or communities to help them to achieve, maintain or regain optimal health as well as the quality of life throughout their lives. Consequently, it forms an integral part of the health care system that helps in achieving better treatment and patient care outcomes. The field of nursing has evolved over the years, thereby leading to the creation of sub-fields such as nursing research. To invent new techniques in nursing or to improve the existing ones, nursing practitioners must engage in regular research work (Bury & Grove, 2008). Even though a large percentage of nurses are aware of the importance of nursing research, some of them hardly participate in it. Besides, some of the nurses have never had the benefit of utilizing new research findings to improve their productivity. These shortcomings can be attributed to several factors such as lack of resources, inadequate knowledge in research, and institutional barriers (Clamp & Gough, 2004). Nursing research can either be qualitative or quantitative. Qualitative research focuses on the subjective meaning of an experience. Quantitative research on the other hand focuses on the measurement, objectivity, and control over the research process (Munhall, 2010). This paper focuses on quantitative nursing research. The procedures involved in quantitative non-experimental nursing research will be discussed alongside its strengths and weaknesses.
Quantitative research can be defined as “a systematic investigation of a nursing or medical phenomenon via statistical, mathematical or computational techniques” (Polit & Beck, 2004). Quantitative research is concerned with the development and application of mathematical models which are used to test hypotheses and theories about the phenomenon under study. Measurement is an integral part of the process since it helps in establishing connections between the empirical observations and the “mathematical expressions of the quantitative relationships” (Funnell & Lawrence, 2008). Typical quantitative research involves the following procedures. Models, theories, and hypotheses are normally generated to help in studying the problem at hand. Measurement methods and instruments must be developed to help in quantifying the factors under study. Data must be collected through methods such as surveys. Once collected, the data is normally analyzed with the aid of statistical software such as SPSS, R, and Stata. Finally, the results are evaluated to provide an understanding of the problem under study. In general, quantitative research involves determining the relationship between the independent and the dependent variables.
Non-experimental research is one that “lacks manipulation of the independent variables by the researcher” (Boswell & Carroon, 2009). This means that the researcher simply studies what occurs naturally with a focus on the relationships between variables. The independent variables are those that cannot or should not be manipulated during the study. They typically represent the factors that influence the phenomenon under study. The dependent variables are those that are influenced by the independent variables. They represent the phenomenon under study.
Conditions for Cause and Effect in Non-experiment Research
To determine the cause and effect of a given phenomenon, the following conditions must be met. First, the variables must be related. Second, the researcher should establish a proper time order in the study (Gorard, 2001). Finally, the relationship between the variables under study must not be as a result of the influence of a third or extraneous variable.
Control over particular variables can be ensured through the following techniques. First, the concept of matching can be used. In this case, the matching variable is the one you intend to control during the study. Second, the extraneous variable can be held constant. For example, to control for gender the research can include only the male in his study. Finally, statistical controls can be used. Statistical techniques such as partial correlation and ANOVA are used in this case (Balnaves & Capati, 2001).
The data used in non-experimental research can differ over time in the following ways. The non-experimental research is said to be cross-sectional if the “data is collected at a single point in time” (Nigel & Pope, 2008). Thus additional data is not collected for conducting follow-up research. The research can also be said to be longitudinal or prospective if data collection is done in two or more time points progressively. This provides an opportunity to compare the results for the two-time points. Finally, the research is said to be retrospective if data is obtained from the past.
Non-experimental research has three main objectives. It can be descriptive, predictive, or explanatory. Descriptive non-experimental research provides a picture of the characteristic of the phenomenon under study. Predictive research aims at forecasting the future status of the dependent variables (Maxifield & Rabbie, 2010). Explanatory research is concerned with the cause and effect relationships. It is used to offer explanations on why and how a phenomenon behaves as it does.
Quantitative research is meant to be an “inferential enterprise whose aim is to uncover collective principles” (Harvey, 2010). This means that quantitative research is concerned with the development of a body of knowledge that can be used to provide explanations to similar situations in the future. Quantitative research is based on the possibility of making inferences from a sample and using the results to generalize to the larger population.
The research questions answered by quantitative research can be divided into three categories namely, descriptive questions, comparative questions, and relating questions. Descriptive questions aim at finding a description of the factors that influence the variables under study. Comparative questions direct the focus of the study towards the analysis of the similarities and differences in the factors or variables under study (Ott & Lognecker, 2008). Finally, relating questions focus on establishing relationships between variables. Each category of the research question is normally structured in a particular way. Besides, the type of research question to be answered determines the design of the quantitative research.
The procedure for conducting quantitative research can be explained as follows. To begin with, the researcher must understand the criteria to be observed in quantitative research. Good quantitative research should meet the following criteria. There should be “clarity and relevance of purpose” (Gorard, 2001) in the study. The problem to be investigated should be researchable. This means that the available research techniques should enable the researcher to investigate the problem. The literature review should be adequate and relevant to provide sufficient and reliable background information about the problem. There should be a match between the research’s purpose, its design as well as the methods used to conduct it (Harvey, 2010). A suitable sample should be used. Such a sample should be big enough and selected through appropriate procedures. The analytical process should be correct to provide reliable findings. Finally, the research findings should be clear to the targeted audience or users of the research findings.
Stages in Quantitative Research
Identifying the Problem
The first step in conducting quantitative research involves identifying the problem to be investigated. Such a problem can be identified from the day-to-day experiences of the nurses. The available literature on various nursing challenges can also help in identifying the problem. It is important to determine whether the problem can be quantified to avoid complications during data analysis (Bury & Grove, 2008).
Since a typical research problem involves many facets, it is usually difficult to use single research to investigate the entire problem. Consequently, the researcher should focus on a particular facet of the problem to enhance the effectiveness of the research findings (Gaul, 2010). The selected facet of the problem thus becomes the purpose of the research. The purpose of the research should be very clear since it influences the design of the research. The purpose can be identified using the SMART criteria. This means that an appropriate research purpose should be “systematic, measurable, attainable, realistic and time-bound” (Gaul, 2010).
Definition of Terms
The terms to be used in the research should be properly defined to enhance the understanding of the research assistants and the consumers of the research findings. Defining the terms to be used in the study is motivated by the fact that the researcher might use a particular term to imply a meaning that is different from the dictionary meaning. Consequently, the researcher should provide both conceptual and operational definitions of terms (Gabor, 2010). Conceptual definitions are the typical meanings of the terms according to the relevant dictionaries. Operational definitions on the other hand are the meanings of the terms according to how they have been used by the researcher.
A literature review involves finding information about the topic of the study from existing literature. This involves reading, understanding, summarizing, and critiquing the available literature. The purpose of conducting a literature review is to update the researcher about his or her topic of study (Boswell & Carroon, 2009). It also provides a basis for developing a theoretical and conceptual framework that will guide the study. The researcher can also be able to compare his findings with those in existing literature at the end of the study (Clamp & Gough, 2004). The main sources of literature include reports of previous research studies, journal articles, and textbooks. It is important to evaluate the relevance and suitability of each source of literature before using it to access reliable information.
Conceptual and Theoretical Framework
The conceptual and theoretical framework that guides the study must be formulated correctly. The selected theory should indicate the relationship between concepts to be used in the study. The conceptual framework is a “diagrammatic and structural presentation of the problem’s hypothesis” (Gorard, 2001). The actual structural presentation of the developed conceptual framework is thus the paradigm of the study.
Having developed the conceptual and theoretical framework, the researcher should then formulate the hypothesis of the study (Gaul, 2010). The research’s hypothesis can take the form of null versus alternative hypothesis or directional versus non-directional hypothesis.
Sampling is the process of determining the part of the population from which data will be collected (Cochran, 2007). Once the population of the study is identified, sampling can be done using probability or non-probability methods. In probability sampling, the members of the population are given equal chances of being recruited. Thus a random method is used to recruit the participants (Chalmers, 2008). In non-probability sampling, the participants are not recruited by chance. They are recruited through a systematic process such as quota sampling or snowball sampling.
Data collection is the process of gathering the desired information from the sample or the participants (Boswell & Carroon, 2009). The most common methods of data collection include questionnaires, interviews, and observations. In the case of questionnaires, the answers can be dichotomized in terms of either ‘yes or no’. A rating scale can also be used. For example on a scale of 1 to 5, 1 can represent poor and 5 represent best. Interviews on the other hand involve structured and unstructured questions.
This is the part of research in which the data collected is used to build a body of knowledge to accept or reject the hypothesis of the study (Cherepanov, 2011). This involves processing the raw data into a meaningful body of knowledge. In quantitative research, data analysis is done through statistical or mathematical procedures (Fruthwrith, 2000). Computer-based statistical software packages are normally used in the analysis.
Interpretation of the Result
The results of the data analysis process must be correctly interpreted by the researcher. The results are usually expressed in numerical terms such as percentages or graphical form which makes the interpretation process easier (Fruthwrith, 2000). Finally, conclusions and recommendations are made based on the interpretations of the results.
Communicating the Findings
This involves disseminating the research findings so that they can reach the targeted audience or the intended users. The research findings can be made available to its consumers through reports, oral presentations, or any form of electronic communication (Nigel & Pope, 2008). Simple and clear language should be used in this process to enhance understanding since not all users of research findings are conversant with technical terms.
Strengths of Quantitative Research
Quantitative research allows the researcher to test existing theories regarding why and how phenomena occur. It also allows the researcher to test the hypothesis that is normally developed before data collection (Ott & Lognecker, 2008). Through the use of random sampling, the researcher can make generalizations on the larger population. This saves the time and resources that could have been used to study the entire population. The findings of quantitative research allow researchers to make predictions on the future status of a phenomenon (Harvey, 2010). This helps in planning or taking timely precautionary measures. Data analysis is relatively easy and less time-consuming in quantitative research due to the use of statistical software. Besides, the findings are normally independent of the researcher. For example, statistical significance can not be directly influenced by the researcher. Finally, it is useful in conducting a study involving large numbers of participants.
Weaknesses of Quantitative Research
The theories used by the researcher might not reflect the participants’ understanding. Hence data collection will be difficult. In some cases, the emphasis on hypothesis and theory testing denies the researcher the opportunity of generating a new theory. Consequently, the researcher can fail to determine the factors that contribute to the occurrence of the phenomenon. The knowledge produced is sometimes “too abstract and general to be used directly” (Polit & Beck, 2004). Thus the users must always be in a position to make inferences from the findings.
Rural Nurses use of Research
The primary aim of this research work was to determine the availability of research findings to nurses working in rural areas (O’Lynn & Luparell, 2009). The secondary aim was to find out how such result findings were being used by the nurses working in the rural areas. It was quantitative research conducted in rural areas of North America. The data was collected from the 800 participants using surveys. Data analysis was done with the aid of statistical techniques.
The philosophical foundation of this study is that rural realities may “create obstacles in accessing and using research-based evidence in practice” (O’Lynn & Luparell, 2009). The foundations are justified since rural nurses and facilities lack adequate resources to enhance access and utilization of research findings which they most need. It is thus possible to conduct quantitative research to find out how many nurses in rural areas can access and use new research findings.
Title and Abstract
The research’s title is fully justified since the researchers managed to determine the extent to which rural nurses can access and utilize new research findings. They also succeeded in finding out the factors that influence access to research findings. The abstract is complete and very informative. It provides details of the research such as the aim, the sample size, research design, the findings, and the conclusions made.
Method and Sample Size
An adequate sample size of 800 nurses was used in the study. The survey instrument used was tested through a pilot study in which 100 nurses from Eastern Montana participated. The response rate for the pilot study was 52%. However, the response rate for the actual study was only 35% (O’Lynn & Luparell, 2009). This reflects the researchers’ inability to motivate the participants to complete the surveys. The low response rate could also be a result of the nurses’ negative attitude towards the research. The participants were recruited from three states namely South Dakota, Oregon, and Montana. Recruiting participants from different states with different situations in rural areas made it possible to make a comparative analysis on the utilization of research findings.
Data analysis was done through statistical procedures via SPSS version 15 software. In particular, descriptive statistics was used to determine the frequencies of items and central tendency measures (O’Lynn & Luparell, 2009). A predictive model was not developed to forecast the use of research findings by rural nurses. A predictive model could have shed light on the trend of research utilization thereby making it easy to formulate policies to promote the use of research in rural areas.
The research succeeded in finding the extent to which research is used by nurses in rural areas. The findings indicate that over fifty percent of the nurses can access new research findings through journals, the internet, and education/ regular training. However, the study did not evaluate the quality or the suitability of the sources of research findings used by the nurses. Besides, the study did not explore the factors that constrain access to research findings and how such factors can be addressed.
Factors Influencing Research Experience among Professional Nurses in the Southern Regional Hospitals of Thailand
The main aim of this research was to determine the factors influencing nurses’ experiences in research. It was quantitative research in which 190 nurses participated (Singchungchai & Chalermwannapory, 2009). The participants were selected through the systematic random sampling method. The study was conducted in hospitals situated in the southern region of Thailand. Data was collected from the participants through questionnaires. Data analysis was done through descriptive and discriminant statistical techniques.
The research was based on the philosophy that ability to carry out research is one of the techniques required to develop effective and quality nursing services. In Thailand, most research work in nursing conducted between 1972 and 1982 was done by graduate students (Singchungchai & Chalermwannapory, 2009). Nurses in public hospitals had the least participation in research work. Thus it is justified to conduct quantitative research to find out the factors that influence nurses’ experiences in research.
Title and Abstract
The title of the research is justified since the researchers succeeded in evaluating the experiences of nurses in research and the factors that influenced such experiences. Besides, clear recommendations on how nurses’ participation in research can be improved have been provided. The abstract is complete and provides all details about the research. It particularly gives information on the research purpose, the sample size, the techniques used, and the results of the data analysis.
Method and Sample Size
A relatively small sample of only 190 nurses was obtained from a population of 925 nurses in the southern region of Thailand (Singchungchai & Chalermwannapory, 2009). All the participants completed and returned the questionnaires. The research was conducted in all four regional hospitals in the southern part of Thailand. However, the tool used was not reposted to check for internal consistency. This undermines the reliability of the results.
Since this was descriptive research, the data was analyzed using descriptive statistical techniques. Discriminant analysis was also used to analyze the data to determine the relationship between the dependent and the independent variables (Singchungchai & Chalermwannapory, 2009). However, a predictive model was not developed to help in forecasting the future trend of the participation of nurses in research.
The research succeeded in determining the factors that influence the experiences or the participation of nurses in research work. It also provides recommendations on how nurses’ participation in research work can be improved. However, it fails to provide a prediction on how the trend in nurses’ participation in research is likely to be in the future.
Nursing research is very important to all practicing nurses. This is based on the fact that it leads to the development of new techniques and information for improving the quality of nursing services. Quantitative research is one of the research designs used by nurses to conduct their studies (Bury & Grove, 2008). It is concerned with the use of mathematical or statistical models to test theories and hypotheses. This involves studying the relationships between the independent and dependent variables. As discussed above the researcher should be conversant with the various stages involved in conducting quantitative research to succeed.
Balnaves, M., & Capati, P. (2001). Introduction to Quantitative Reserach Methods. London: Sage Publishing.
Boswell, C., & Carroon, S. (2009). Introduction to Nursing Research. Philadelphia: Jones & Bartlet Learning.
Bury, N., & Grove, S. (2008). The Practice of Nursing Reserach. New York: Elsevier.
Chalmers, J. (2008). Sampling Techniques. New York: John Wiley and Sons.
Cherepanov, E. (2011). Stochastic Methods of Data Analysis. Applied Econometrics, 22(2) , 48-61.
Clamp, C., & Gough, S. (2004). Resources for Nursing Research. New York: John Wiley and Sons.
Cochran, W. (2007). Sampling Techniques. New Delhi: Wiley India.
Fruthwrith, R. (2000). Data Analysis Techniques. London: Cambridge University Press.
Funnell, R., & Lawrence, K. (2008). Tabbner’s Nursing Research Care. New York: McGraw-Hill.
Gabor, M. (2010). Descriptive methods of Data Analysis. Management, 5(3), 401-432.
Gaul, B. (2010). Theory, Methods and Application in Data Analysis. Advances in Data Analysis and Classification, 10(2), 40-46.
Gorard, S. (2001). Quantitative Methods in Education Research. London: British Library.
Harvey, B. (2010). Social Research Methods. New York: Sage Publishing.
Maxifield, M., & Rabbie, E. (2010). Reserach Methods. New York: Cengage Learning.
Munhall, P. (2010). Nursing Research. Boston: Jones & Bartlet Learning.
Nigel, B., & Pope, D. (2008). quantitative Methods for Research. New York: John Wiley and Sons.
O’Lynn, C., & Luparell, S. (2009). Rural Nurses’ Reserach Use. Journal of Rural Nursing and Health Care, 9(1) , 201-210.
Ott, L., & Lognecker, M. (2008). An Introduction to Statistical Methods and Data Analysis. New York: Cengage Learning.
Polit, D., & Beck, T. (2004). Nursing Research. Philadelphia: Lippincott Williams & Wilkins.
Singchungchai, P., & Chalermwannapory, S. (2009). Factors Influencing Reserach Experinece among Professional Nurses in the Southern Regional Hospitals of Thailand. Human Resources for Health Development Journal, 3(2), 139-147.